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QuantSeq 3' 测序与 Salmon 联合使用,为高通量 RNA 表达分析提供了一种快速、可靠的方法。

QuantSeq. 3' Sequencing combined with Salmon provides a fast, reliable approach for high throughput RNA expression analysis.

机构信息

Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, UNSW Sydney, New South Wales, Australia.

Telethon Kids Institute Australia, The University of Western Australia, Perth, Australia.

出版信息

Sci Rep. 2019 Dec 11;9(1):18895. doi: 10.1038/s41598-019-55434-x.

DOI:10.1038/s41598-019-55434-x
PMID:31827207
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6906367/
Abstract

RNA-Seq is increasingly used for the diagnosis of patients, targeting of therapies and for single cell transcriptomics. These applications require cost effective, fast and reliable ways of capturing and analyzing gene expression data. Here we compared Lexogen's QuantSeq which captures only the 3' end of RNA transcripts and Illumina's TruSeq, using both Tophat2 and Salmon for gene quantification. We also compared these results to microarray. This analysis was performed on peripheral blood mononuclear cells stimulated with Poly (I:C), a viral mimic that induces innate antiviral responses. This provides a well-established model to determine if RNA-Seq and QuantSeq identify the same biological signatures. Gene expression levels in QuantSeq and RNA-Seq were strongly correlated (Spearman's rho ~0.8), Salmon and Tophat2 (Spearman's rho > 0.9). There was high consistency in protein coding genes, non-concordant genes had a high proportion of shorter, non-coding features. RNA-Seq identified more differentially expressed genes than QuantSeq, both methods outperformed microarray. The same key biological signals emerged in each of these approaches. We conclude that QuantSeq, coupled with a fast quantification method such as Salmon, should provide a viable alternative to traditional RNA-Seq in many applications and may be of particular value in the study of the 3'UTR region of mRNA.

摘要

RNA-Seq 越来越多地用于患者诊断、靶向治疗和单细胞转录组学。这些应用需要具有成本效益、快速和可靠的方法来捕获和分析基因表达数据。在这里,我们比较了 Lexogen 的 QuantSeq,它只捕获 RNA 转录本的 3'端,以及 Illumina 的 TruSeq,使用 Tophat2 和 Salmon 进行基因定量。我们还将这些结果与微阵列进行了比较。这项分析是在经 Poly (I:C) 刺激的外周血单核细胞上进行的,Poly (I:C) 是一种模拟病毒的物质,可诱导先天抗病毒反应。这为确定 RNA-Seq 和 QuantSeq 是否识别相同的生物学特征提供了一个成熟的模型。QuantSeq 和 RNA-Seq 中的基因表达水平高度相关(Spearman's rho~0.8),Salmon 和 Tophat2 之间也高度相关(Spearman's rho>0.9)。在蛋白编码基因中具有高度一致性,不一致的基因具有较高比例的较短、非编码特征。RNA-Seq 比 QuantSeq 鉴定出更多差异表达的基因,这两种方法都优于微阵列。这些方法都出现了相同的关键生物学信号。我们得出结论,QuantSeq 与 Salmon 等快速定量方法相结合,在许多应用中应该可以替代传统的 RNA-Seq,并且在研究 mRNA 的 3'UTR 区域时可能特别有价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/cf8eb7c9ffe2/41598_2019_55434_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/dea63b025820/41598_2019_55434_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/943e38042f9d/41598_2019_55434_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/39607df1d745/41598_2019_55434_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/98fdd0ed1c33/41598_2019_55434_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/95e460386f73/41598_2019_55434_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/d7a248354bec/41598_2019_55434_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/4cf146b096c7/41598_2019_55434_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/cf8eb7c9ffe2/41598_2019_55434_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/dea63b025820/41598_2019_55434_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/943e38042f9d/41598_2019_55434_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/39607df1d745/41598_2019_55434_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/98fdd0ed1c33/41598_2019_55434_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/95e460386f73/41598_2019_55434_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/d7a248354bec/41598_2019_55434_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/4cf146b096c7/41598_2019_55434_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07ca/6906367/cf8eb7c9ffe2/41598_2019_55434_Fig8_HTML.jpg

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